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Record W2774201531 · doi:10.1186/s12913-017-2641-1

Perceptions about data-informed decisions: an assessment of information-use in high HIV-prevalence settings in South Africa

2017· article· en· W2774201531 on OpenAlexfundno aff
Edward Nicol, Debbie Bradshaw, Jeannine Uwimana-Nicol, Lilian Dudley

Bibliographic record

VenueBMC Health Services Research · 2017
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersAfrican Population and Health Research CenterSouth African Medical Research CouncilInternational Development Research CentreUniversiteit StellenboschJohn D. and Catherine T. MacArthur Foundation
KeywordsHealth informaticsMedicineNursing researchHealth administrationObservational studyInformation systemEnvironmental healthData collectionPublic healthQualitative propertyDescriptive statisticsNursingFamily medicineMedical emergencyComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Information-use is an integral component of a routine health information system and essential to influence policy-making, program actions and research. Despite an increased amount of routine data collected, planning and resource-allocation decisions made by health managers for managing HIV programs are often not based on data. This study investigated the use of information, and barriers to using routine data for monitoring the prevention of mother-to-child transmission of HIV (PMTCT) programs in two high HIV-prevalence districts in South Africa. METHODS: We undertook an observational study using a multi-method approach, including an inventory of facility records and reports. The performance of routine information systems management (PRISM) diagnostic 'Use of Information' tool was used to assess the PMTCT information system for evidence of data use in 57 health facilities in two districts. Twenty-two in-depth interviews were conducted with key informants to investigate barriers to information use in decision-making. Participants were purposively selected based on their positions and experience with either producing PMTCT data and/or using data for management purposes. We computed descriptive statistics and used a general inductive approach to analyze the qualitative data. RESULTS: Despite the availability of mechanisms and processes to facilitate information-use in about two-thirds of the facilities, evidence of information-use (i.e., indication of some form of information-use in available RHIS reports) was demonstrated in 53% of the facilities. Information was inadequately used at district and facility levels to inform decisions and planning, but was selectively used for reporting and monitoring program outputs at the provincial level. The inadequate use of information stemmed from organizational issues such as the lack of a culture of information-use, lack of trust in the data, and the inability of program and facility managers to analyze, interpret and use information. CONCLUSIONS: Managers' inability to use information implied that decisions for program implementation and improving service delivery were not always based on data. This lack of data use could influence the delivery of health care services negatively. Facility and program managers should be provided with opportunities for capacity development as well as practice-based, in-service training, and be supported to use information for planning, management and decision-making.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.004
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.149
GPT teacher head0.526
Teacher spread0.377 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations53
Published2017
Admission routes1
Has abstractyes

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